System and method for managing a cache pool

ABSTRACT

In one embodiment, a system includes a processor and a memory communicatively coupled to the processor. The processor is configured to receive a write request associated with a cache pool, which comprises a plurality of disks. The write request comprises data associated with the write request. The processor is additionally configured to select a first disk from the plurality of disks using a life parameter associated with the first disk. The processor is further configured to cause the data associated with the write request to be written to the first disk.

TECHNICAL FIELD

This disclosure relates generally to information handling systems andmore particularly to an improved system and method for managing a cachepool.

BACKGROUND

As the value and use of information continues to increase, individualsand businesses seek additional ways to process and store information.One option available to users is information handling systems. Aninformation handling system generally processes, compiles, stores,and/or communicates information or data for business, personal, or otherpurposes thereby allowing users to take advantage of the value of theinformation. Because technology and information handling needs andrequirements vary between different users or applications, informationhandling systems may also vary regarding what information is handled,how the information is handled, how much information is processed,stored, or communicated, and how quickly and efficiently the informationmay be processed, stored, or communicated. The variations in informationhandling systems allow for information handling systems to be general orconfigured for a specific user or specific use such as financialtransaction processing, airline reservations, enterprise data storage,or global communications. In addition, information handling systems mayinclude a variety of hardware and software components that may beconfigured to process, store, and communicate information and mayinclude one or more computer systems, data storage systems, andnetworking systems.

The concept of caching data in a cache has long been employed ininformation handling systems. A cache can include a block of memory fortemporarily storing data that may be likely to be accessed again.Maintaining a cache of data likely to be accessed again may increasesystem performance. For example, an information handling system may becoupled to a storage array via a network, but may maintain a storagecache local to the information handling system. Data read from orwritten to the remote storage array that is likely to be accessed again(e.g., data that is most-recently used and/or most-frequently used) maybe stored to the local cache, so that the information handling systemcan access the cached data from the cache, rather than accessing thedata from the remote storage array which may take a longer period oftime, due to latency inherent in performing input/output operations overa network.

SUMMARY

In one embodiment, a method includes receiving a write requestassociated with a cache pool comprising a plurality of disks. The writerequest comprises data associated with the write request. The methodadditionally includes selecting a first disk from the plurality of disksusing a life parameter associated with the first disk. The methodfurther includes causing the data associated with the write request tobe written to the first disk.

In one embodiment, a system includes a processor and a memorycommunicatively coupled to the processor. The processor is configured toreceive a write request associated with a cache pool, which comprises aplurality of disks. The write request comprises data associated with thewrite request. The processor is additionally configured to select afirst disk from the plurality of disks using a life parameter associatedwith the first disk. The processor is further configured to cause thedata associated with the write request to be written to the first disk.

Certain embodiments of the present disclosure may provide one or moretechnical advantages. The industry has increasingly implemented cachesusing solid-state storage devices. However, one well-known disadvantageof solid-state storage devices are the limited number of times data canbe written to the devices compared to other forms of storage.Solid-state storage devices often employ flash memory. Typically, a cellof a flash-based solid-state storage device can be only be erased (andtherefore written) a limited number of times before it fails.Accordingly, over time a sufficient number of cells may fail such thatthe solid-state storage device may be incapable of writing further data.A technical advantage of one embodiment includes causing disks to wearat approximately the same or a similar rate, reducing or eliminating therisk that one disk may be overused and fail substantially sooner thanother disks in the system (e.g., one disk receives 1%, 2%, 5%, or 10%more writes to it than the other disks in the system). Another technicaladvantage of one embodiment includes reducing the cost of replacingdisks that fail substantially earlier than others in system.

Other technical advantages of the present disclosure will be readilyapparent to one skilled in the art from the following figures,descriptions, and claims. Moreover, while specific advantages have beenenumerated above, various embodiments may include all, some, or none ofthe enumerated advantages.

BRIEF DESCRIPTION OF THE DRAWINGS

Reference is now made to the following description taken in conjunctionwith the accompanying drawings, wherein like reference numbers representlike parts.

FIG. 1 is a block diagram of an example of an information handlingsystem in accordance with some embodiments of the present disclosure.

FIG. 2A illustrates an example of a database comprising a set ofparameters associated with nodes in the information handling system ofFIG. 1.

FIG. 2B illustrates an example of a database comprising a set ofpriority scores associated with nodes in the information handling systemof FIG. 1.

FIG. 3 is a flowchart describing an example of managing a cache pool.

DETAILED DESCRIPTION

FIG. 1 illustrates a block diagram of an example of information handlingsystem 100 in accordance with some embodiments of the presentdisclosure. In particular embodiments, system 100 may include one ormore nodes 102 a-c that are coupled to network 160. Node 102 a includescache 103 a, node 102 b includes cache 130 b and node 102 c includescache 103 c. Caches 103 a-c each include a plurality of disks and areincluded in cache pool 170. Nodes 102 a-c may also include memorymodules 120 a-c. Memory modules 120 a-c may include parameters 122 a-c,which may include information about disks in caches 130 a-130 c. Forexample, a life parameter may how many times data may be written to adisk and a usage parameter may represent the available storage spaceremaining on disk. Memory modules 120 a-c may further include priorityscores 124 a-c, which scores each disk in cache pool 170 based onparameters 122 a-c associated with the disks to select a disk that thesystem should write data to. System 100 is configured to receive a writerequest associated with cache pool 170, select a first disk from cachepool 170 using a life parameter (e.g., one of parameters 122 a-c)associated with the first disk, and cause the data associated with thewrite request to be written to the first disk.

Nodes 102 a-c, in some embodiments, may comprise a server sled, a servermodule, a server node, a server blade, or any suitable structure capableof housing node components. Nodes 102 a-c may comprise processors 110a-c, memory modules 120 a-c, caches 130 a-c, user interfaces 150 a-c,and network interfaces 140 a-c. It should be understood that theparticular illustrated components of each node 102 a-c are examples onlyand that additional, fewer, and/or alternative components may bepresent. For example, each node 102 a-c may include multiple processors110 a-c or memory modules 120 a-c.

In particular embodiments, user interfaces 150 a-c include hardware,software, or both, providing one or more interfaces for communicationbetween information handling system 100 and one or more I/O devices.Information handling system 100 may include one or more of these I/Odevices, where appropriate. One or more of these I/O devices may enablecommunication between a person and information handling system 100. Asan example and not by way of limitation, an I/O device may include akeyboard, keypad, microphone, monitor, mouse, printer, scanner, speaker,still camera, stylus, tablet, touch screen, trackball, video camera,another suitable I/O device or a combination of two or more of these. AnI/O device may include one or more sensors. This disclosure contemplatesany suitable I/O devices and any suitable user interfaces 150 for them.Where appropriate, user interfaces 150 a-c may include one or moredevice or software drivers enabling processors 110 a-c to drive one ormore of these I/O devices. Although this disclosure describes andillustrates a particular user interface, this disclosure contemplatesany suitable user interface.

Network interfaces 140, in some embodiments, include hardware, software,or both providing one or more interfaces for communication (such as, forexample, packet-based communication) between information handling system100 and one or more other information handling systems 100 or one ormore networks. As an example and not by way of limitation, networkinterface 140 may include a network interface controller or card (NIC)or network adapter for communicating with an Ethernet or otherwire-based network or a wireless NIC (WNIC) or wireless adapter forcommunicating with a wireless network, such as a WI-FI network. Thisdisclosure contemplates any suitable network and any suitable networkinterface 140 for the network. As an example and not by way oflimitation, information handling system 100 may communicate with an adhoc network, a personal area network (PAN), a local area network (LAN),a wide area network (WAN), a metropolitan area network (MAN), or one ormore portions of the Internet or a combination of two or more of these.One or more portions of one or more of these networks may be wired orwireless. As an example, information handling system 100 may communicatewith a wireless PAN (WPAN) (such as, for example, a BLUETOOTH WPAN), aWI-FI network, a WI-MAX network, a cellular telephone network (such as,for example, a Global System for Mobile Communications (GSM) network),or other suitable wireless network or a combination of two or more ofthese. Information handling system 100 may include any suitable networkinterfaces 140 a-c for any of these networks, where appropriate.Although this disclosure describes and illustrates a particular networkinterface, this disclosure contemplates any suitable communicationinterface.

In particular embodiments, buses 112 a-c include hardware, software, orboth coupling components of information handling system 100 to eachother. As an example and not by way of limitation, buses 112 a-c mayinclude an Accelerated Graphics Port (AGP) or other graphics bus, anEnhanced Industry Standard Architecture (EISA) bus, a front-side bus(FSB), a HYPERTRANSPORT (HT) interconnect, an Industry StandardArchitecture (ISA) bus, an INFINIBAND interconnect, a low-pin-count(LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, aPeripheral Component Interconnect (PCI) bus, a PCI-Express (PCIe) bus, aserial advanced technology attachment (SATA) bus, a Video ElectronicsStandards Association local (VLB) bus, or another suitable bus or acombination of two or more of these. Although this disclosure describesand illustrates a particular bus, this disclosure contemplates anysuitable bus or interconnect.

Processors 110 a-c, in some embodiments, may comprise any system,device, or apparatus operable to interpret and/or execute programinstructions and/or process data. Processors 110 a-c may include one ormore: microprocessors, microcontrollers, digital signal processors(DSP), graphical processing units (GPU), application specific integratedcircuits (ASIC), or another digital or analog circuitry configured tointerpret and/or execute program instructions and/or process data. Insome embodiments, processors 110 a-c may interpret and/or executeprogram instructions and/or process data stored locally (e.g., in memorymodules 120 a-c). In the same or alternative embodiments, processors 110a-c may interpret and/or execute program instructions and/or processdata stored remotely. This disclosure contemplates processors 110 a-cincluding any suitable number of any suitable internal registers, whereappropriate. Where appropriate, processors 110 a-c may include one ormore arithmetic logic units (ALUs); be a multi-core processor; orinclude one or more processors 110. Although this disclosure describesand illustrates a particular processor, this disclosure contemplates anysuitable processor.

Caches 130 a-c, in some embodiments, may comprise any system, device, orapparatus operable to facilitate access to data stored in a storagesystem (e.g., a file system, a database, a hard drive, or other suitablestorage systems). In particular embodiments, caches 130 a-c are operableto store copies of such data so that such data may be accessed fasterthrough caches 130 a-c than by accessing the storage system which storessuch data. Caches 130 a-c may be communicatively coupled to processors110 a-c. For example, caches 130 a-c may be physically within nodes 102a-c and may be coupled to processors 110 a-c using buses 112 a-c. Asanother example, caches 130 a-c may be physically stored in a separatelocation and may be communicatively coupled to processors 110 a-cthrough an internal network. Caches 130 a-c may include one or moredisks. Disks, in some embodiments, may comprise solid state drives(SSDs) or any drive operable to store information associated with awrite request. Caches 130 a-c may include any number of disks. Forexample, cache 130 a may comprise four disks (disk A, disk B, disk C,and disk D); cache 130 b may comprise two disks (disk E and disk F); andcache 130 c may comprise three disks (disk G, disk H, and disk I).Although illustrated with a specific number of disks, system 100 mayinclude any number of disks within caches 130 a-c.

In some embodiments, nodes 102 a-c may cause data to be written to adisk in either a local cache or a remote cache. In some embodiments, alocal cache may be physically stored within nodes 102 a-c and/or may belocated on the same internal network as a host node (e.g., 102 a). Eachof nodes 102 a-c may have access to one or more local caches and one ormore remote caches. For example, cache 130 a may be a local cache tonode 102 a and a remote cache to nodes 102 b and 102 c. As anotherexample, cache 130 b may be a local cache to node 102 b and a remotecache to nodes 102 a and 102 c. As an additional example, cache 130 cmay be a local cache to node 102 c and a remote cache to nodes 102 a and102 b. All caches 130 a-c that are available for processors 110 a-c tocause data to be written on may comprise cache pool 170. Although thisdisclosure describes an illustrates a particular number of caches 130a-c, system 100 may include any number of caches.

Memory modules 120 a-c may, in various embodiments, comprise any system,device, or apparatus operable to retain and/or retrieve programinstructions and/or data (e.g., computer-readable media). Memory modules120 a-c may comprise one or more modules; such modules can includerandom access memory (RAM), electrically erasable programmable read-onlymemory (EEPROM), a PCMCIA card, flash memory, magnetic storage,opto-magnetic storage, and/or a suitable selection and/or array ofvolatile or non-volatile memory that retains data after power to itsassociated information handling system, such as information handlingsystem 100, is powered down. In some embodiments memory modules 120 a-cmay be implemented using any of these techniques, including techniquesdifferent from each other. In some embodiments, memory modules 120 a-ccomprise parameters 122 a-c and priority scores 124 a-c.

Parameters 122 a-c, in some embodiments, may include any number ofparameters associated with the disks in caches 130 a-c and indicatingcharacteristics and/or properties of disks. Parameters 122 a-c, in someembodiments, may include a life parameter, which may represent thenumber of times data has been written to disk, the remaining number oftimes data can be written to disk, or any information indicating whendisk is likely to fail. Disks, in some embodiments, may comprise SSDsthat may be rated and marketed according to a maximum program and erase(P/E) cycles, known as the endurance rating (e.g., 5K, 10K, 100K).Because SSDs have a limited predetermined life (e.g., number of P/Ecycles available), a life parameter may track the remaining write life(e.g., number of P/E cycles) available. The life parameter of each diskmay be represented in any suitable format, for example, as a number ofremaining cycles or a percentage of remaining life. Life parameters foreach disk may be stored in memory modules 120 a-c in any suitable format(e.g., as a table, matrix, or database). Parameters 122 a-c, in someembodiments, may also include usage parameters for disks. Usageparameter may represent the available storage space remaining on disk.The usage parameter of each disk may be presented in any suitableformat, for example, as a percentage of space currently used on disk, asa percentage of space available on disk, as a value of space availableon disk, or as a value of space used on disk. Usage for each disk may bestored in memory modules 120 a-c in any suitable format (e.g, in atable, matrix, or database). FIG. 2A illustrates database 222 indicatinglife parameters and usage parameters for each disk in cache pool 170.Processors 110 a-c may access parameters 122 a-c in memory modules 120a-c when selecting a first disk to cause data to be written to, asdescribed below. By utilizing the life parameter when selecting a diskto write to, processors 110 a-c may reduce or eliminate the risk thatone of disks may be written to more frequently than other disks invarious embodiments. By seeking to have the life parameters among alldisks in cache pool 170 be similar to each other, processors 110 a-c mayallow for a more even distribution of remaining life among disks. Thiscan reduce or eliminate the risk that one disk may fail substantiallysooner than other disks (e.g., one disk may receive 10% more writes thanother disks). This can increase the life of caches 130 a-c withoutsignificantly impacting the performance of caches 130 a-c.

Priority scores 124, in some embodiments, may comprise a score for eachof the plurality of disks in cache pool 170. Priority scores 124 a-c mayindicate which disk has the highest priority, and thus which diskprocessors 110 a-c should select to cause data from a write request tobe written on. Priority scores 124 a-c may be calculated by processors110 a-c using parameters 122 a-c. For example, processors 110 a-c maydetermine a first priority based on a disk's current life parametervalue, determine a second priority based on a disk's current usageparameter value, and combine these priorities to calculate a priorityscore. An administrator of system 100 may determine the priorityassociated with each parameter value. FIG. 2B illustrates database 224indicating priority scores 124 a-c for each disk in cache pool 170.Processors 110 a-c may access priority scores 124 a-c in memory modules120 a-c when selecting a first disk to cause data to be written to, asdescribed below.

In one example of operation of information handling system 100, userinterface may receive a write request from a user or administrator ofsystem 100. Processors 110 a-c may determine a life parameter of one ormore disks in the local cache (e.g., cache 130 a for processor 110 a)and in one or more remote caches (e.g., caches 130 b and 130 c).Processors 110 a-c may calculate priority scores 124 a-c for each diskof cache pool 170 and select the disk with the highest priority.Processors 110 a-c then causes the data associated with the writerequest to be written to the disk with the highest priority.

In some embodiments, processors 110 a-c receive parameters 122 a-cassociated with a plurality of disks. Parameters 122 a-c may comprise alife parameter, a usage parameter, and any other parameters associatedwith a disk. In some embodiments, processors 110 a-c may receiveparameters 122 a-c in different ways. For example, each time processors110 a-c receive a write request, processors 110 a-c may requestparameters from disks in a local cache (e.g., 130 b for processor 110 b)and communicate with processors 110 a and 110 c to receive parameters122 a-c from disks in remote caches (e.g., 130 c and 130 a). As anotherexample, processors 110 a-c may receive parameters 122 a-c on a regulartime interval (for example, hourly, daily, weekly, or monthly).Processors 110 a-c may also receive parameters 122 a-c each time thatdata is written to one of disks A-I in cache pool 170 (e.g., any time aparameter value changes or is updated). In some embodiments, processors110 a-c may receive priority scores 124 a-c when receiving parameters122 a-c. In some embodiments, processors 110 a-c may receive parameters122 a-c and may calculate priority scores 124 a-c itself.

In some embodiments, processors 110 a-c calculate a priority score forthe plurality of disks using one or more parameters from parameters 122a-c associated with the plurality of disks. Processors 110 a-c may referto a priority matrix to determine priority scores 124 a-c. An example ofthe priority matrix that may be used to calculate priority scores foreach disk is shown in Table 1 below.

TABLE 1 priority matrix Life User-Defined Usage User-Defined parameterPriority Parameter Priority 80-100%  .1 80-100%  5 60-80% .2 60-80% 440-60% .3 40-60% 3 20-40% .4 20-40% 2  0-20% .5  0-20% 1As shown in Table 1, life parameter may be indicated as a percentage ofremaining life of a disk. As the remaining life increases (highpercentage), the user-defined priority assigned to the range decreases,corresponding to a higher priority. For example, if a disk has 100%remaining write life, then it would receive a priority of 0.1,indicating that it should be selected above other disks. As shown inTable 1, usage parameter may be indicated as a percentage of space usedon a disk. As the usage increases (high percentage), the user-definedpriority assigned to the range increases, corresponding to a lowerpriority. For example, if a disk has used 98% of its current space, thedisk would receive a priority of 5, indicating that it should not beselected above other disks due to the low space available. Table 1represents an example of the priorities that may be assigned based onthe values of the various parameters associated with a disk.Administrator of system 100 may define the priorities in any suitablemanner.

Processors 110 a-c may use parameters 122 a-c and a priority matrix (anexample of which is shown above in Table 1) in order to calculatepriority scores 124 a-c for each disk. Referring to FIG. 2A, usingdatabase 222, which shows parameter values for the disks in cache pool170, processors 110 a-c may calculate priority scores 124 a-c. Forexample, disk A has a life parameter value of 60-80%, which correspondsto a priority of 0.2 based on priority matrix in Table 1 above. Disk Ahas a usage parameter of 20-40%, which corresponds to a priority of 2based on priority matrix in Table 1 above. Processors 110 a-c may thencombine the two priorities from each parameter to determine the priorityscore. Processors 110 a-c may combine the two priorities throughmultiplication, addition, averaging, or any suitable operation todetermine the priority score. Continuing the example from above,processors 110 a-c may add the life parameter priority of 0.2 to theusage parameter priority of 2.0 to determine a priority score of 2.2 fordisk A. FIG. 2B illustrates an example of priority score matrix 224,which shows the calculated priority scores 124 a-c for the disks incache pool 170.

In some embodiments, processors 110 a-c determine a disk with thegreatest priority in cache pool 170. In some embodiments, processors 110a-c may determine the disk with the lowest priority score (e.g., closestto 0), to determine the disk with the highest priority. Continuing theexample from above and referring to FIG. 2B, disk A may have the lowestpriority score of the disks in local cache 130 a. Disk A has lowerpriority scores than disks B, C, and D because it has a large percentageof remaining life (as indicated by its life parameter of 60-80%) and alow current usage percentage (as indicated by its usage parameter of20-40%), resulting in a low priority score of 2.2

In some embodiments, processors 110 a-c may determine that writing to adisk in a local cache (e.g., 130 c for node 102 c) is preferred towriting to a disk in a remote cache (e.g., 130 a for node 102 c). If alocal cache is preferred, processors 110 a-c may select one of the disksin the local cache even if a disk in a remote cache has a higherpriority. For example, referring to database of priority scores 224illustrated in FIG. 2B, processor 110 a (of node 102 a) may select diskA as the disk to use for a write request even though disk H of node 102c has a lower priority score, and thus a higher priority. In someembodiments, processors 110 a-c may determine that a local cache is notpreferred. For example, processors 110 a-c may select disk H as the diskwith the greatest priority based on its score of 1.5, which is thelowest score listed in database 224, indicating that it has the highestpriority.

For the purposes of this disclosure, an information handling system mayinclude any instrumentality or aggregate of instrumentalities operableto compute, calculate, determine, classify, process, transmit, receive,retrieve, originate, switch, store, display, communicate, manifest,detect, record, reproduce, handle, or utilize any form of information,intelligence, or data for business, scientific, control, or otherpurposes. For example, an information handling system may be a personalcomputer (e.g., desktop or laptop), tablet computer, mobile device(e.g., personal digital assistant (PDA) or smart phone), server (e.g.,blade server or rack server), a network storage device, or any othersuitable device, and may vary in size, shape, performance,functionality, and price. The information handling system may includerandom access memory (RAM), one or more processing resources such as acentral processing unit (CPU) or hardware or software control logic,ROM, and/or other types of nonvolatile memory. Additional components ofthe information handling system may include one or more disk drives, oneor more network ports for communicating with external devices as well asvarious input and output (I/O) devices, such as a keyboard, a mouse,touchscreen and/or a video display. The information handling system mayalso include one or more buses operable to transmit communicationbetween the various hardware components.

This disclosure contemplates any suitable number of information handlingsystems 100. Where appropriate, information handling system 100 mayinclude one or more information handling systems 100, be unitary ordistributed, span multiple locations, span multiple machines, spanmultiple data centers, or reside in a cloud, which may include one ormore cloud components in one or more networks. Where appropriate, one ormore information handling systems 100 may perform without substantialspatial or temporal limitation one or more steps of one or more methodsdescribed or illustrated herein. As an example and not by way oflimitation, one or more information handling systems 100 may perform inreal time or in batch mode one or more steps of one or more methodsdescribed or illustrated herein. One or more information handlingsystems 100 may perform at different times or at different locations oneor more steps of one or more methods described or illustrated herein,where appropriate. Although this disclosure describes and illustrates aparticular information handling system having a particular number ofparticular components in a particular arrangement, this disclosurecontemplates any suitable information handling system having anysuitable number of any suitable components in any suitable arrangement.

For the purposes of this disclosure, computer-readable media may includeany instrumentality or aggregation of instrumentalities that may retaindata and/or instructions for a period of time. Computer-readable mediamay include, without limitation, storage media, such as a direct accessstorage device (e.g., a hard disk drive or floppy disk); a sequentialaccess storage device (e.g., a tape disk drive); a compact disk; CD-ROM;DVD; random access memory (RAM); read-only memory (ROM); electricallyerasable programmable read-only memory (EEPROM); solid state drives(SSDs) such as Single Level Cell (SLC), Multi Level Cell (MLC),enterprise MLC (eMLC), and/or flash memory; as well as communicationsmedia, such as wires, optical fibers, microwaves, radio waves, and otherelectromagnetic and/or optical carriers; and/or any combination of theforegoing.

Modifications, additions, or omissions may be made to the systemsdescribed herein without departing from the scope of the disclosure. Forexample, information handling system 100 may include any number of nodes102 a-c, cache pools 170, and networks 160. The components may beintegrated or separated. Moreover, the operations may be performed bymore, fewer, or other components. Additionally, the operations may beperformed using any suitable logic comprising software, hardware, and/orother logic.

FIG. 3 is a flowchart describing an example of managing a cache pool bysystem 100 of FIG. 1. At step 302, in some embodiments, processor 110 amay receive a write request from user interface 150 a. The write requestmay have data associated with it to be written to one or more of thedisks of cache pool 170.

At step 304, in some embodiments, processor 110 a determines whether afairness cycling policy applies. A fairness cycling policy may be apolicy that writes data to each disk based on a predetermined rotationof the disks (e.g., the disks may be written to in a sequence). If afairness cycling policy applies, step 306 may be performed and if afairness cycling policy does not apply, step 308 may be performed. Ifprocessor 110 a determines that a fairness cycling policy applies instep 304, then processor 110 a writes the data corresponding to thewrite request received in step 302 to a next disk in cache pool 170 atstep 306. For example, using a fairness cycling policy, processor 110 amay determine a next disk by determining which disk is next in thepredetermined rotation of the disks. As another example, if the localcache is preferred, processor 110 may determine a next disk bydetermining which disk of the disks in the local cache is next in thepredetermined rotation of the disks. After writing the data to the nextdisk in step 306, the method ends.

If processor 110 a determines at step 304 that a fairness cycling policydoes not apply, processor 110 a determines whether the local cache ispreferred at step 308, in some embodiments. If the local cache ispreferred, step 310 may be performed and if a local cache is notpreferred, step 326 may be performed. In some embodiments, a user oradministrator of system 100 may select a setting that the local cache ispreferred. For example, for processor 110 a, local cache may comprisecache 130 a, including disks A, B, C and D. In some embodiments,processor 110 a may perform step 308, determining whether the localcache is preferred, prior to step 304, determining whether a fairnesscycling policy applies. For example, processor 110 a may determine thata local cache is preferred, determine that a fairness cycling policyapplies, and write the data corresponding to the write request to a nextdisk in the local cache pool. As another example, processor 110 maydetermine that a local cache is not preferred, determine that a fairnesscycling policy applies, and write the data corresponding to the writerequest to a next disk in the remote cache pool.

At step 310, in some embodiments, processor 110 a determines whether thelocal cache, for example, cache 130 a, is full. Processor 110 a maydetermine the usage of each of the disks by polling the disks withincache 130 a to determine whether any of the disks in cache 130 a containavailable space. Processor 110 a may access the stored parameters 122 ain memory module 120 a that may include a database of usage parametersfor each disk in cache 130 a. FIG. 2A illustrates an example of database222 storing parameters 122 a. If processor 110 a determines that a localcache is full in step 310, step 326 may be performed in which processor110 a examines the disks of remote caches (e.g., caches 130 b and 130c). If processor 110 a determines that the local cache is not full(e.g., at least one of the disks in cache 130 a has a current usage lessthan 100% or otherwise has sufficient capacity to store informationassociated with the write request), step 312 may be performed.

At step 312, in some embodiments, processor 110 a determines lifeparameters for the plurality of disks in the local cache. Processor 110a may determine the life parameter for the plurality of disks, such asdisks A, B, C, and D, in any number of ways. For example, processor 110a may poll each of the disks within cache 130 a to determine the lifeparameters. As another example, processor 110 a may access memorymodules 120 a-c that store parameters 122 a. An example of parameters122 a is depicted in FIG. 2A in matrix 222.

At step 314, in some embodiments, processor 110 a determines usageparameters for the plurality of disks in cache 130 a. Processor 110 amay determine the usage parameters by polling the disks and/or byaccessing parameters 122 a in memory 120 a, similar to the techniquethat processor 110 a uses to determine the life parameters at step 312.

At step 316, in some embodiments, processor 110 a calculates priorityscores for the plurality of disks in local cache 130 a. Processor 110 amay calculate priority scores 124 a using the life parameters and theusage parameters determined at steps 312 and 314, respectively. Forexample, processor 110 a may calculate the priority score of disk B inlocal cache 130 a as 4.4. Disk B may have a remaining life parameter of20-40% and a current usage parameter of 60-80%, as shown database 222 ofFIG. 2A. Processor 110 a may use any suitable scoring technique toassociate a score with life parameter and usage parameter. For example,a priority associated with a 20-40% life parameter may be 0.4 and apriority associated with usage parameter 60-80%, may be 4.0 (asillustrated above in Table 1). Continuing the example, processor 110 amay add the life parameter priority (0.4) and the usage parameterpriority (4.0) to determine the priority score of disk B as 4.4.Processor 110 a may use any suitable scoring technique and associate anysuitable priorities with certain parameter values. An example ofpriority scores associated with each life parameter and usage parameteris shown in Table 1 above. In some embodiments, processor 110 a maycalculate the priority score for each of the disks in cache pool 170,for example a priority score for each of disks A, B, C, D, E, F, G, H,and I. An example of priority scores database 224 that may be stored inmemory 120 a is illustrated in FIG. 2B.

At step 318, in some embodiments, processor 110 a determines a disk withthe greatest priority based on priority scores 124 a of the disks.Processor 110 a may compare priority scores 124 a for each disk (e.g.,disks A, B, C, D) to determine which disk has the highest priority.Continuing the example from above, disk A may have a priority score of2.2, disk B may have a priority score of 4.4, disk C may have a priorityscore of 4.5 and disk D may have a priority score of 5.3. In thisexample, processor 110 a may select disk A as the disk with the lowestpriority score, which corresponds with the highest priority disk.

At step 320, in some embodiments, processor 110 a determines whether oneor more disks each have the highest priority. For example, if disk A hasa priority of 2.2, disk B has a priority of 4.4, disk C has a priorityof 2.2, and disk D has a priority of 5.3, then disk A and disk C bothhave the same priority score of 2.2. Because 2.2 is the lowest priorityscore of the disks in local cache 130 a (which corresponds to thehighest priority), processor 110 a may determine that more than one diskhas the highest priority. If at step 320 processor 110 a determines thatone or more disks have the highest priority, for example, disk A anddisk C having the same priority score of 2.2, then processor 110 a maywrite the data to a first available disk with the highest priority instep 322. Processor 110 a may determine the first available disk bydetermining which disk is next in the predetermined rotation of thedisks. If at step 320, processor 110 a determines that only one disk hasthe highest priority (e.g., disk A's priority score of 2.2 results in ithaving the highest priority), then processor 110 a, at step 324, writesthe data associated with the write request received in step 302 to diskA in various embodiments. After writing the data either to the firstavailable disk in step 322 or to the disk with the greatest priority instep 324, the method ends.

If processor 110 a determines that the local cache is not preferred instep 308, or that the local cache is full in step 310, the methodcontinues to step 326. At step 326, in some embodiments, processor 110 adetermines a life parameter for a plurality of disks in a remote cache.A remote cache may be any cache that is not located on node 102 a. Forexample, referring to FIG. 1, cache 130 b and cache 130 c would beremote caches to node 102 a. At step 328, in some embodiments, processor110 a may determine a usage parameter for the plurality of disks in theremote cache. For example, processor 110 a may communicate withprocessors 110 b and 110 c about caches 130 b and 130 c through network160. In some embodiments, determining life and usage parameters of aplurality of disks in steps 326 and 328 can be performed using one ormore of the techniques discussed above with respect to steps 312-314.

At step 330, in some embodiments, processor 110 a may calculate priorityscores for the plurality of disks in the remote cache. For example,processor 110 a may determine that disk E of remote cache 130 b has apriority score of 5.2 and that disk F of remote cache 130 b has apriority score of 4.1. Processor 110 a may further determine thepriority scores of the disks located in cache 130 c. For example, disk Gmay have a priority score of 3.4, disk H may have a priority score of1.5 and disk I may have a priority score of 1.3. In some embodiments,calculating a priority score for the disks in remote caches in step 330can be performed using one or more of the techniques discussed abovewith respect to step 316.

At step 332, in some embodiments, processor 110 a may determine the diskwith the greatest priority based on the priority scores calculated instep 330. Continuing the example from above, processor 110 a maydetermine that Disk H has the lowest priority score of the disks in theremote caches 130 b and 130 c, and thus that Disk H has the highestpriority. In some embodiments, determining the disk with the greatestpriority in step 332 can be performed using one or more techniquesdiscussed above with respect to step 318.

In some embodiments, processor 110 a determines whether one or moredisks each have the highest priority in step 334. Determining whetherone or more disks each have the highest priority in step 334 can beperformed using one or more of the techniques discussed above withrespect to step 320. Continuing the example from above, processor 110 amay determine that only one disk has the highest priority (e.g., Disk Hwith a priority score of 1.5). If processor 110 a determines that onlyone disk has the highest priority, then processor 110 a causes the datato be written to the selected disk with the greatest priority (e.g.,disk H) in step 338. Processor 110 a may send a message to networkinterface 140 c through network interface 140 a via network 160 so thatprocessor 110 c may write the data to disk H located in cache 130 c. If,at step 334, processor 110 a determines that at least two disks have thehighest priority, processor 110 a causes the data from the write requestto be written to a first available disk with the highest priority instep 336 in some embodiments. For example, if disk E has a priorityscore of 1.5 and disk H has a priority score of 1.5, resulting in bothof them having the highest priorities of the disks in cache pool 170,then processor 110 a may select disk E as the first available disk.After processor 110 a causes the data to be written to either the firstavailable disk with the highest priority in step 336 or to the selecteddisk to use for a write request in step 338, the method ends.

Modifications, additions, or omissions may be made to the methodsdescribed in FIG. 3 without departing from the scope of the disclosure.For example, the steps may be combined, modified, or deleted whereappropriate, and additional steps may be added. For example, processors110 a-c may determine the disk with the greatest priority in step 318based on the life parameters of the disks. In this example, steps 314and 316, which determine usage parameters and calculate priority scoresmay be omitted. Additionally, the steps may be performed in any suitableorder without departing from the scope of the present disclosure. Whilediscussed as processors (e.g., 110 a, 110 b, and 110 c) and theircomponents performing the steps, any suitable component of informationhandling system 100 may perform one or more of the steps.

Although the present disclosure has been described with severalembodiments, a myriad of changes, variations, alterations,transformations, and modifications may be suggested to one skilled inthe art, and it is intended that the present disclosure encompass suchchanges, variations, alterations, transformations, and modifications asfall within the scope of the appended claims.

What is claimed is:
 1. A method comprising: receiving a write requestassociated with a cache pool comprising a plurality of disks, the writerequest comprising data associated with the write request; selecting afirst disk from the plurality of disks using a life parameter associatedwith the first disk; and causing the data associated with the writerequest to be written to the first disk.
 2. The method of claim 1,wherein the cache pool is a local cache and, the method furthercomprising: determining that the local cache is preferred; determiningthat each disk in the local cache is full; receiving a set of parametersassociated with a plurality of disks in a remote cache, the set ofparameters comprising the life parameter; calculating a priority scorefor the plurality of disks in the remote cache using the life parametersassociated with the plurality of disks in the remote cache; based on thepriority score, determining a disk with the greatest priority, the diskwith the greatest priority having a highest priority of the plurality ofdisks in the remote cache; determining that at least two disks of theplurality of disks in the remote cache each have the highest priority;wherein selecting the first disk from the plurality of disks comprisesselecting a first available disk of the at least two disks of theplurality of disks in the remote cache with the highest priority; andwherein causing the data associated with the write request to be writtento the first disk comprises causing the data associated with the writerequest to be written to the first available disk.
 3. The method ofclaim 1, further comprising: calculating a priority score for theplurality of disks using the life parameters associated with theplurality of disks; based on the priority score, determining a disk withthe greatest priority; and wherein selecting the first disk from theplurality of disks comprises selecting the disk with the greatestpriority.
 4. The method of claim 3, further comprising: determining thatat least two disks of the plurality of disks each have the highestpriority; wherein selecting the first disk from the plurality of diskscomprises selecting a first available disk of the at least two disks ofthe plurality of disks with the highest priority; and wherein causingthe data associated with the write request to be written to the firstdisk comprises causing the data associated with the write request to bewritten to the first available disk with the highest priority.
 5. Themethod of claim 1, wherein the cache pool is a local cache and, themethod further comprising: local cache determining whether the localcache is preferred; determining whether each disk in the local cache isfull; if the local cache is preferred and each disk in the local cacheis not full, then determining the first disk using the life parametercomprises determining a local disk using the life parameter, the localdisk being in the local cache; and if the local cache is preferred andeach disk in the local cache is full, then determining the first diskusing the life parameter comprises determining a remote disk using thelife parameter, the remote disk being in a remote cache.
 6. The methodof claim 1, further comprising: receiving a second write requestassociated with the cache pool; determining that a fairness cyclingpolicy applies; in response to determining that the fairness cyclingpolicy applies, selecting a second disk, the second disk identifiedusing the fairness cycling policy; and causing the data corresponding tothe write request to be written to the second disk.
 7. The method ofclaim 1, further comprising: receiving a set of parameters associatedwith a plurality of disks, the set of parameters comprising a lifeparameter and a usage parameter; and updating stored parameters for eachof the plurality of disks using the received set of parameters.
 8. Aninformation handling system, comprising: a memory; a processorcommunicatively coupled to the memory, the processor configured to:receive a write request associated with a cache pool comprising aplurality of disks, the write request comprising data associated withthe write request; select a first disk from the plurality of disks usinga life parameter associated with the first disk; and cause the dataassociated with the write request to be written to the first disk. 9.The system of claim 8, wherein the cache pool is a local cache and, theprocessor is further configured to: determine that the local cache ispreferred; determine that each disk in the local cache is full; receivea set of parameters associated with a plurality of disks in a remotecache, the set of parameters comprising the life parameter; calculate apriority score for the plurality of disks in the remote cache using thelife parameters associated with the plurality of disks in the remotecache; based on the priority score, determine a disk with the greatestpriority, the disk with the greatest priority having a highest priorityof the plurality of disks in the remote cache; determine that at leasttwo disks of the plurality of disks in the remote cache each have thehighest priority; wherein selecting the first disk from the plurality ofdisks comprises selecting a first available disk of the at least twodisks of the plurality of disks in the remote cache with the highestpriority; and wherein causing the data associated with the write requestto be written to the first disk comprises causing the data associatedwith the write request to be written to the first available disk. 10.The system of claim 8, wherein the processor is further configured to:calculate a priority score for the plurality of disks using the lifeparameters associated with the plurality of disks; based on the priorityscore, determine a disk with the greatest priority; and whereinselecting the first disk from the plurality of disks comprises selectingthe disk with the greatest priority.
 11. The system of claim 10, whereinthe processor is further configured to: determine that at least twodisks of the plurality of disks each have the highest priority; whereinselecting the first disk from the plurality of disks comprises selectinga first available disk of the at least two disks of the plurality ofdisks with the highest priority; and wherein causing the data associatedwith the write request to be written to the first disk comprises causingthe data associated with the write request to be written to the firstavailable disk with the highest priority.
 12. The system of claim 8,wherein the cache pool is a local cache and, the processor is furtherconfigured to: determine whether the local cache is preferred; determinewhether each disk in the local cache is full; if the local cache ispreferred and each disk in the local cache is not full, then determiningthe first disk using the life parameter comprises determining a localdisk using the life parameter, the local disk being in the local cache;and if the local cache is preferred and each disk in the local cache isfull, then determining the first disk using the life parameter comprisesdetermining a remote disk using the life parameter, the remote diskbeing in a remote cache.
 13. The system of claim 8, wherein theprocessor is further configured to: receive a second write requestassociated with the cache pool; determine that a fairness cycling policyapplies; in response to determining that the fairness cycling policyapplies, select a second disk, the second disk identified using thefairness cycling policy; and cause the data corresponding to the writerequest to be written to the second disk.
 14. The system of claim 8,wherein the processor is further configured to: receive a set ofparameters associated with a plurality of disks, the set of parameterscomprising a life parameter and a usage parameter; and update storedparameters for each of the plurality of disks using the received set ofparameters.
 15. A non-transitory computer-readable medium includingcomputer-executable instructions encoded in the computer-readablemedium, the instructions, when executed by a processor, operable to:receive a write request associated with a cache pool comprising aplurality of disks, the write request comprising data associated withthe write request; select a first disk from the plurality of disks usinga life parameter associated with the first disk; and cause the dataassociated with the write request to be written to the first disk. 16.The computer-readable medium of claim 15, wherein the cache pool is alocal cache and the computer-executable instructions, when executed by aprocessor, are further operable to: determine that the local cache ispreferred; determine that each disk in the local cache is full; receivea set of parameters associated with a plurality of disks in a remotecache, the set of parameters comprising the life parameter; calculate apriority score for the plurality of disks in the remote cache using thelife parameters associated with the plurality of disks in the remotecache; based on the priority score, determine a disk with the greatestpriority, the disk with the greatest priority having a highest priorityof the plurality of disks in the remote cache; determine that at leasttwo disks of the plurality of disks in the remote cache each have thehighest priority; wherein selecting the first disk from the plurality ofdisks comprises selecting a first available disk of the at least twodisks of the plurality of disks in the remote cache with the highestpriority; and wherein causing the data associated with the write requestto be written to the first disk comprises causing the data associatedwith the write request to be written to the first available disk. 17.The computer-readable medium of claim 15, the computer-executableinstructions, when executed by a processor, further operable to:calculate a priority score for the plurality of disks using the lifeparameters associated with the plurality of disks; based on the priorityscore, determine a disk with the greatest priority; and whereinselecting the first disk from the plurality of disks comprises selectingthe disk with the greatest priority.
 18. The computer-readable medium ofclaim 17, the computer-executable instructions, when executed by aprocessor, further operable to: determine that at least two disks of theplurality of disks each have the highest priority; wherein selecting thefirst disk from the plurality of disks comprises selecting a firstavailable disk of the at least two disks of the plurality of disks withthe highest priority; and wherein causing the data associated with thewrite request to be written to the first disk comprises causing the dataassociated with the write request to be written to the first availabledisk with the highest priority.
 19. The computer-readable medium ofclaim 15, wherein the cache pool is a local cache and thecomputer-executable instructions, when executed by a processor, arefurther operable to: determine whether the local cache is preferred;determine whether each disk in the local cache is full; if the localcache is preferred and each disk in the local cache is not full, thendetermining the first disk using the life parameter comprisesdetermining a local disk using the life parameter, the local disk beingin the local cache; and if the local cache is preferred and each disk inthe local cache is full, then determining the first disk using the lifeparameter comprises determining a remote disk using the life parameter,the remote disk being in a remote cache.
 20. The computer-readablemedium of claim 15, the computer-executable instructions, when executedby a processor, further operable to: receive a second write requestassociated with the cache pool; determine that a fairness cycling policyapplies; in response to determining that the fairness cycling policyapplies, select a second disk, the second disk identified using thefairness cycling policy; and cause the data corresponding to the writerequest to be written to the second disk.